Modeling Heteroscedasticity in the Presence of Outliers in Discrete-Time Stochastic Series
Emmanuel Alphonsus Akpan*,
Lasisi K. E. and
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Emmanuel Alphonsus Akpan*: Department of Mathematical Science, AbubakarTafawaBalewa University, Bauchi, Nigeria
Lasisi K. E.: Department of Mathematical Science, AbubakarTafawaBalewa University, Bauchi, Nigeria
Ali Adamu: Federal College of Education (Tech.), Gombe, Gombe State, Nigeria
Academic Journal of Applied Mathematical Sciences, 2018, vol. 4, issue 7, 61-76
The aim of this study is to examine the effects of outliers on the specification and efficiency of heteroscedastic models fitted to the daily closing share price returns series of two outstanding banks in Nigeria from January 3, 2006 to November 24, 2016. The series consists of 2690 observations for each bank. The data were obtained from the Nigerian Stock Exchange.Â GARCH(2,0) model with respect to student-t error distribution and GARCH(1,1) model under normal error distribution were successfully fitted to the outlier contaminated series of Diamond bank and United bank for Africa accordingly. On the contrary, EGARCH(1,1) model with respect to student-t error distribution adequately captured the changing variance in the outlier adjusted series of the two banks considered. Substantial evidence revealed that the presence of outliers in returns series leads to model misspecification and adjusting for such outliers ensures model efficiency.
Keywords: ARCH effects; Model efficiency; Nigerian banking sector; Volatility. (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:arp:ajoams:2018:p:61-76
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